Crop residue based field operation adjustment

ABSTRACT

A crop residue monitoring system may include a harvester, a camera to capture an image of crop residue generated by the harvester, an analytical unit to derive a value for a crop residue parameter of the crop residue based upon an optical analysis of the image and a control unit to adjust a subsequent field operation based upon the value of the crop residue parameter.

RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.16/517,482, filed Jul. 19, 2019, the disclosure of which is herebyincorporated by reference in its entirety.

BACKGROUND

Crop residue is a byproduct of a crop harvesting operation. Crop residuemay include straw, chaff or other unwanted portions of a crop plantfollowing threshing and/or separation processes by a harvester. Cropresidue may additionally include other biomass such as weeds, weed seedsand the like. Such residue is often discharged from the harvester.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 schematically illustrates portions of an example crop residuemonitoring system.

FIG. 2 is a flow diagram of an example method for monitoring cropresidue and adjusting field operations based on the crop residue.

FIG. 3 is a block diagram of an example controller for monitoring cropresidue.

FIG. 4 is a flow diagram of an example method for deriving values for acrop residue parameter based upon captured images of crop residue.

FIG. 5 is a flow diagram of an example method for deriving values for acrop residue parameter based upon captured images of crop residue.

FIG. 6 is a diagram illustrating an example crop residue monitoringsystem including a harvester.

FIG. 7 is an enlarged view of an example camera mount for the harvesterof FIG. 6 .

FIG. 8 is an enlarged view of another example camera mount for theharvester of FIG. 6 .

Throughout the drawings, identical reference numbers designate similar,but not necessarily identical, elements. The figures are not necessarilyto scale, and the size of some parts may be exaggerated to more clearlyillustrate the example shown. Moreover, the drawings provide examplesand/or implementations consistent with the description; however, thedescription is not limited to the examples and/or implementationsprovided in the drawings.

DETAILED DESCRIPTION OF EXAMPLES

Disclosed are example crop residue monitoring systems, methods andmachine-readable mediums that monitor crop residue generated by aharvester and use such information to adjust subsequent fieldoperations. The disclosed systems, methods and mediums may utilize acamera to capture an image of the crop residue generated by theharvester. An analytical unit derives a value for the crop residueparameter of the crop residue based upon an optical analysis of theimage. A control unit utilizes the value of the crop residue parameterto adjust a subsequent field operation. As a result, the subsequentfield operations may be more attuned to the current crop residueconditions.

In some implementations where the crop residue being analyzed is cropresidue that has already been discharged from the harvester, the cameraused to capture the image of the crop residue may be that of asatellite, drone, tillage machine or other platform distinct from theharvester generating the crop residue. The camera may be of varioustypes including, but not limited to, an optical camera, a thermalimaging camera, a radar-based camera, a hyperspectral camera and a lightimaging detection and radiation (LIDAR) camera. In some implementations,the camera used to capture the image of the crop residue, prior todischarge or after discharge from the harvester, is carried by theharvester itself. In one implementation, the camera is supported so asto capture images of the crop residue prior to discharge of the cropresidue from the harvester. For example, in some implementations, thecamera may be located so as to capture images of the crop residue as itis being blown from a sieve or chaffer towards a rear residue spreaderof the harvester. In some implementations, camera may be located so asto capture images of the crop residue as it is being directed from astraw walker or threshing rotor towards a rear residue spreader of theharvester. In some implementations, the camera may be located such tocapture images of the crop residue after is undergone chopping, butbefore being spread by the rear residue spreader of the harvester. Inyet other implementations, the camera may be located so as captureimages of the crop residue after the crop residue has been discharged.In some implementations, multiple cameras may be utilized to captureimages of the crop residue more than one of the above describedlocations or stages.

In implementations where images of the crop residue are captured atmultiple different stages or locations, the controller derive multiplevalues for the crop residue parameter at the different stages. In someimplementations, different subsequent field operations may be adjustedbased upon the value of the crop residue parameter at different stages.For example, the controller may adjust a first subsequent fieldoperation based upon the value of the crop residue parameter at a firststage or location and may adjust a second different subsequent fieldoperation based upon the value of the crop residue parameter at a secondstage or location. In some implementations, the controller may adjust asubsequent field operation based upon an aggregation of values for thecrop residue parameter taken at different stages or locations. In someimplementations, the controller may apply different predetermined oroperator selected weightings to the different crop residue parametervalues taken at the different stages or locations.

In some implementations, the controller may utilize the derived valuesfor the crop residue parameter to generate a field map linking differentderived values to different geo-referenced locations in a field. Thefield map may be stored. The stored field map may be consulted to adjustsubsequent field operations at the different geo-referenced locations inthe field.

In one implementation, the subsequent field operations adjusted by thecontroller or adjusted by controller using the generated field map maycomprise subsequent operations to the same geo-referenced regions bydifferent agricultural machines other than the harvester. For example,subsequent tillage settings for tillage machines may be adjusted basedupon the value of the crop residue parameter. Subsequent spraying orplanting operations may be adjusted based upon the value of the cropresidue parameter at different geo-referenced locations or regions.

In some implementations, the settings of the agricultural machine mayremain the same, but the parameter of a subsequent applied material maybe adjusted based upon the value of the crop residue parameter. Forexample, a type, density or other characteristic of seed, of appliedherbicide, of applied insecticide, of applied fertilizer or of otherapplied materials may be adjusted based upon the value of the cropresidue parameter.

In yet other implementations, the operational settings of the harvesteritself during a subsequent harvesting season, during the same harvestingseason or during traversal of the harvester across the same field may beadjusted based upon the value of the crop residue parameter. Forexample, operational settings of the harvester itself minutes or hoursafter the value for the crop residue parameter value has been derived,while harvester is traversing the same field, may be adjusted based uponthe derived crop residue parameter value. Examples of such operationssettings include, but are not limited to, chopper speed, chopper power,harvester speed, harvester feed rate, chopper counter knife position,header height, spreader speeds, spreader vein positions, threshingspeed, cleaning speed, threshing clearance, separator discharge vanepositions. In some implementations, the different derived crop residueparameter values may be displayed for an operator, wherein the operatormay make additional or alternative manual adjustments to the harvesteritself during harvesting.

The crop residue parameter for which values may be derived include, butare not limited to, at least one of chop size, crop residue moisture,crop residue constituents and crop residue dispersion. In oneimplementation, the values may be derived by the analytical unitoptically identifying individual pieces of crop residue and determiningvalues for the individual pieces of crop residue. For example, theanalytical unit may measure a length of each of the pieces of cropresidue, wherein the value of the crop residue parameter may be basedupon a count of the number of pieces having each of a plurality oflengths. The values may be numerical values or may be a categorizationbased upon the numerical values. In some implementations, the value ofthe crop residue parameter may comprise a crop residue parametercategory, wherein the analytical unit comprises a neural network thatderives the category for the crop residue parameter by comparing theimage to a plurality of other images having assigned categories.

In some implementations, the analytical unit may derive different valuesfor the crop residue parameter across a width of a row of dischargedcrop residue and/or along the length of the discharged row of cropresidue across the field. Such information may be linked togeo-referenced data (acquired through a geo-referencing system such asglobal positioning satellite (GPS) based geo-referencing system) to forma crop residue field map that may be used for adjusting subsequent fieldoperations. For example, a first portion of a width of a row ofdischarge crop residue may have a first derived value for a particularcrop residue parameter while a second portion of the width of the row ofdischarge crop residue may have a second derived value for theparticular crop residue parameter different than the first derivedvalue. Likewise, the row or widthwise portions of the row discharged ata first geo-referenced location at a first point in time may have afirst derived value for the particular crop residue parameter whereasthe row or widthwise portions of the row discharged at a secondgeo-referenced location (downstream or down field from the firstgeo-referenced location) at a second later point in time may have asecond derived value for the particular crop residue parameter. Byderiving different geo-referenced crop residue parameter values acrossthe width of a row of discharged crop residue, field operations may beadjusted based upon information having a higher degree of resolution. Byderiving different geo-referenced crop residue parameter values alongdifferent portions of the length of a row of crop residue, at differentpoints in time as a harvester traverses a field, subsequent fieldoperations may be adjusted to accommodate changing conditions as aharvester moves across a field.

FIG. 1 schematically illustrates portions of an example crop residuemonitoring system 20. Crop residue monitoring system 10 utilizes acamera to capture an image of the crop residue generated by theharvester. An analytical unit than derives a value for the crop residueparameter of the crop residue based upon an optical analysis of theimage. A control unit utilizes the value of the crop residue parameterto adjust a subsequent field operation. As a result, the subsequentfield operations may be more attuned to the current crop residueconditions. As shown by FIG. 1 , system 10 comprises harvester 22,camera 24, analytical unit 26 and control unit 50.

Harvester 22 comprise an agricultural machine that separates crop plantsfrom the growing medium and that further processes the crop plants toseparate the targeted portion of the crop plant, such as grain, fromunwanted portions of the crop plant, such as straw, chaff or other cropresidue. In one implementation, harvester 22 comprises a combineharvester that separates grain, such as corn, wheat, oats or the likefrom the remaining crop residue 53 using a threshing mechanism and acleaning mechanism. The threshing mechanism may comprise a straw walkeror threshing rotor. The cleaning mechanism may comprise a chaffer orsieve through which the grain falls and from which the crop residue,such as straw are chaff, is blown rearwardly for discharge andspreading. In some implementations, harvester may additionally include achopper which chops the crop residue prior to his discharge.

Camera 24 captures images of the crop residue 53 generated by harvester22. In one implementation, camera 24 capture the image of the crop afterit has been discharged and spread by harvester 22. In such animplementation, camera 10 4B provided by a satellite, drone, tillagemachine or other platform distinct from the harvester generating thecrop residue. In some implementations, the camera 24 used to capture theimage of the crop residue 53, prior to discharge or after discharge fromthe harvester, is carried by the harvester 22 itself. In oneimplementation, the camera 24 is supported so as to capture images ofthe crop residue prior to discharge of the crop residue from theharvester. For example, in some implementations, the camera 24 may belocated so as to capture images of the crop residue as it is being blownfrom a sieve or chaffer towards a rear residue spreader of theharvester. In some implementations, camera 24 may be located so as tocapture images of the crop residue as it is being directed from a strawwalker or threshing rotor towards a rear residue spreader of theharvester. In some implementations, the camera 24 may be located such tocapture images of the crop residue after the crop residue has undergonechopping, but before the chopped crop residue has been spread by therear residue spreader of the harvester. In yet other implementations,camera 24 may be located so as capture images of the crop residue afterthe crop residue has been discharged. In some implementations, multiplecameras 24 may be utilized to capture images of the crop residue at morethan one of the above described stages.

Analytical unit 26 comprises a processing unit that follows instructionscontained on a non-transitory computer-readable or machine-readablemedium. Analytical unit 26 receives the captured image 55 from camera 24and derives a value 57 for a crop residue (CR) parameter of the cropresidue based upon an optical analysis of the image. The crop residueparameter for which a value 57 may be derived include, but are notlimited to, at least one of chop size, crop residue moisture, cropresidue constituents and crop residue dispersion. In one implementation,the values may be derived by the analytical unit optically identifyingindividual pieces of crop residue and determining values for theindividual pieces of crop residue. For example, the analytical unit maymeasure a length of each of the pieces of crop residue, wherein thevalue of the crop residue parameter may be based upon a count of thenumber of pieces having each of a plurality of lengths. In someimplementations, the value of the crop residue parameter may comprise acrop residue parameter category, wherein the analytical unit comprisingneural network that derives the category for the crop residue parameterby comparing the image to a plurality of other images having assignedcategories.

In some implementations, the analytical unit 24 may derive differentvalues for the crop residue parameter across a width of a row ofdischarged crop residue and/or along the length of the discharged row ofcrop residue across the field. Such information may be linked togeo-referenced data (acquired through a geo-referencing system such asGPS based geo-referencing system) to form a crop residue field map thatmay be used for adjusting subsequent field operations. For example, afirst portion of a width of a row of discharge crop residue may have afirst derived value for a particular crop residue parameter while asecond portion of the width of the row of discharge crop residue mayhave a second derived value for the particular crop residue parameterdifferent than the first derived value. Likewise, the row or widthwiseportions of the row discharged at a first geo-referenced location at afirst point in time may have a first derived value for the particularcrop residue parameter whereas the row or widthwise portions of the rowdischarged at a second geo-referenced location (downstream or down fieldfrom the first geo-referenced location) at a second later point in timemay have a second derived value for the particular crop residueparameter. By deriving different geo-referenced crop residue parametervalues across the width of a row of discharged crop residue, fieldoperations may be adjusted based upon information having a higher degreeof resolution. By deriving different geo-referenced crop residueparameter values along different portions of the length of a row of cropresidue, at different points in time as a harvester traverses a field,subsequent field operations may be adjusted to accommodate changingconditions even as a harvester moves across a field.

Control unit 50 comprises a processing unit that follows instructionscontained on a non-transitory machine-readable medium. In oneimplementation, control unit 50 is part of a different agriculturalmachine, other than harvester 22, that carries out a subsequent fieldoperation 59. In one implementation, the subsequent field operation 59adjusted by the controller may comprise subsequent operations to thesame geo-referenced regions by different agricultural machines otherthan the harvester 22. For example, subsequent tillage settings fortillage machines may be adjusted based upon the value of the cropresidue parameter. Subsequent spraying or planting operations may beadjusted based upon the value of the crop residue parameter at differentgeo-referenced locations or regions. In some implementations, thesettings of the agricultural machine having the control unit 50 mayremain the same, but the parameter of a subsequent applied material maybe adjusted by control unit 50 based upon the value of the crop residueparameter. For example, a type, density or other characteristic of seed,of applied herbicide, of applied insecticide, of applied fertilizer orof other applied materials may be adjusted based upon the value of thecrop residue parameter.

In some implementations, control unit 50 may be part of harvester 22.Control unit 50 may adjust the operational settings of the harvester 22itself during a subsequent harvesting season, during the same harvestingseason or during the same pass of the harvester across the same fieldmay be adjusted based upon the value of the crop residue parameter. Forexample, operational settings of the harvester 22 itself minutes orhours after the value for the crop residue parameter value has beenderived, while harvester is traversing the same field, may be adjustedbased upon the derived crop residue parameter value. Examples of suchoperations settings include, but are not limited to, chopper speed,chopper power, harvester speed, harvester feed rate, chopper counterknife position, header height, spreader speeds, spreader vane positions,threshing speed, cleaning speed, threshing clearance, and sieve louverpositions. In some implementations, the different derived crop residueparameter values may be displayed for an operator, wherein the operatormay make additional or alternative manual adjustments to the harvesteritself during harvesting.

In yet other implementations, control unit 50 is a remote controllerthat provides control signals harvester 22 and/or the other agriculturalmachine. Control unit 50 utilizes the derived crop residue parametervalue to output control signals adjusting a subsequent field operation.In some implementations, control unit 50, as part of harvester 22 or asa remote controller, utilize the derived crop residue parameter valueoutput by analytical unit 26 to generate a field map linking differentgeo-referenced regions to different crop residue parameter values. Forexample, harvester 22 may carry a geo-referencing device, such as aglobal positioning satellite transceiver, wherein the derived cropresidue parameter values received from analytical unit 26 are linked tothe associated location or region of the field as provided by thegeo-referencing device. The generated crop residue field map may be usedas a basis for adjusting or controlling subsequent field operations tothe particular geo-referenced regions.

FIG. 2 is a flow diagram of an example method 100 for managing fieldoperations using crop residue parameter values or crop residueinformation. Method 100 is described in the context of being carried outby system 20. However, it should be appreciated that method 100 maylikewise be carried out by any of the other described implementations.

As indicated by block 104, camera 24 captures an image of crop residue53 generated by a harvester 22. The image may be captured at a point intime before or after discharge of the crop residue by the harvester. Insome implementations, camera 24 may capture images of the crop residueat multiple different locations inside of the harvester as well asoutside of the harvester. The images may be captured by camera carriedby the harvester, by an airborne camera or by an agricultural machinethat subsequently crosses the field.

As indicated by block 108, analytical unit 26 derives a value 57 for acrop residue parameter of the crop residue generated by the harvesterbased upon an optical analysis of the crop residue image 55. The cropresidue parameter for which values may be derived include, but are notlimited to, at least one of chop size, crop residue moisture, cropresidue constituents and crop residue dispersion. In one implementation,the values may be derived by the analytical unit optically identifyingindividual pieces of crop residue and determining values for theindividual pieces of crop residue. For example, the analytical unit maymeasure a length of each of the pieces of crop residue, wherein thevalue of the crop residue parameter may be based upon a count of thenumber of pieces having each of a plurality of lengths. In someimplementations, the value of the crop residue parameter may comprise acrop residue parameter category, wherein the analytical unit comprisingneural network that derives the category for the crop residue parameterby comparing the image to a plurality of other images having assignedcategories.

In one implementation the value comprises a numerical statistic such asaverage residue/straw length. In another implementation, the valuecomprises a categorization of the crop residue such as a type of cropresidue, percent of different types of crop residue found in the imageof the like. In another implementation, the value comprises acategorization of the crop residue in terms of processing of the cropresidue such as under processed, over processed and the like, whereinthe “processing” refers to the degree to which the crop residue has beenchanged or reduced in size by the harvester.

In implementations where the value comprises a numerical statistic, thevalue may be derived by optically identifying individual pieces of cropresidue, individual pieces of straw, chaffer the like in measuring acharacteristic of the individual pieces, such as the length of theindividual pieces using optical analysis. Such identification may becarried out by applying various optical filters to the image todistinguish between individual pieces and then measuring the individualpieces using the detected edges of the individual pieces and the scaleof the image being analyzed. The statistical value may be generated bycounting the various pieces of a given length range or other sizedrange. The statistical value may be output or may be compared against athreshold, wherein a categorization of the crop residue is output basedupon the comparison of the statistical value to the threshold.

In some implementations, control unit 50 may comprise a neural network.The neural network may derive a category for the crop residue parameterby comparing the image to a plurality of other images having preassignedcategory values. In one implementation, the preassigned category valuesmay be developed during a training phase. The training phase may be aone time occurrence or may be repeatedly carried out in response tooperator requests, in response to sensed triggering events or afterpredefined lapses of time or acreage traversed.

In one implementation, the training phase may comprise receiving imagesthat have ground truth category labels. For example, persons maypersonally assign category labels to given images of crop residue. Theneural network forming control unit 50 may then optically analyze thesame images of crop residue and identify various category criteria forthe different categories or labels based upon an optical analysis of theimages and the ground truth category labels.

The training phase may also involve at least one verification andadjustment phase, wherein control unit 50 receives a second set ofimages that also have been given ground truth category labels. Controlunit 50 may then apply the identifying aid category criteria to labelthe second images with analytical unit-based category labels. Theseanalytical unit-based category labels may be compared against thehuman-based category labels to see how close the analytical unit-basedcategory labels correspond to the human-based category labels. Basedupon this comparison, the identified category criteria may be adjusted.This process may be iteratively repeated until the analytical unit-basedcategory labels for a given set of images sufficiently match orcorrespond to the human-based category labels for the same set ofimages.

As indicated by block 112, control unit 50 may adjust a subsequent fieldoperation based upon the values of the crop residue parameter. In oneimplementation, the subsequent field operations adjusted by the controlunit 50 or adjusted by control unit 50 using the generated field map maycomprise subsequent operations to the same geo-referenced regions bydifferent agricultural machines other than the harvester. For example,subsequent tillage settings for tillage machines may be adjusted basedupon the value of the crop residue parameter. Subsequent spraying orplanting operations may be adjusted based upon the value of the cropresidue parameter at different geo-referenced locations or regions.

In some implementations, the settings of the agricultural machine mayremain the same, but the parameter of a subsequent applied material maybe adjusted based upon the value of the crop residue parameter. Forexample, a type, density or other characteristic of seed, of appliedherbicide, of applied insecticide, of applied fertilizer or of otherapplied materials may be adjusted based upon the value of the cropresidue parameter.

In yet other implementations, the operational settings of the harvesteritself during a subsequent harvesting season, during the same harvestingseason or during traversal of the harvester across the same field may beadjusted based upon the value of the crop residue parameter. Forexample, operational settings of the harvester itself minutes or hoursafter the value for the crop residue parameter value has been derived,while harvester is traversing the same field, may be adjusted based uponthe derived crop residue parameter value. Examples of such operationssettings include, but are not limited to, chopper speed, chopper power,harvester speed, harvester feed rate, chopper counter knife position,header height, spreader speeds, spreader vane positions, threshingspeed, cleaning speed, threshing clearance, blower speed and sievelouver positions. In some implementations, the different derived cropresidue parameter values may be displayed for an operator, wherein theoperator may make additional or alternative manual adjustments to theharvester itself during harvesting.

FIG. 3 is a block diagram illustrating an example controller 150 thatmay carry out method 100. Controller 150 serves as both analytical unit26 and control unit 50 described above. Controller 150 comprisesprocessing unit 152 in a non-transitory machine-readable medium 154.Processing unit 152 comprises logic circuit components they carry outinstructions provided in the computer/machine-readable medium 154.

Medium 154 comprises a physical memory device, such as a hard diskdrive, a flash memory, a service class memory or the like, for storingboth data and instructions. Medium 154 contains analytical instructions156 and control instructions 158. Analytical instructions 166 carry outthe functions described above with respect analytical unit 26.Analytical instructions 156 direct processing unit 152 to analyze imagescaptured by camera 24 and to derive a value for at least one cropresidue parameter of the crop residue depicted in the images. Controlinstructions 158 carry out the functions described above with respect tocontrol unit 50. Control instructions 158 use the at least one derivedcrop residue parameter value to adjust a field operation that issubsequent to the capturing of the crop residue images. Controlinstructions 158 may direct processing unit 162 to compare the derivedvalues for the at least one crop residue parameter against variousthresholds, wherein the comparison may result in an adjustment to anoperational setting of the harvester 22, an adjustment to theoperational setting of an agricultural machine other than harvester 22crossing the same geo-referenced regions or an adjustment to the type orquantity of material applied to a field. In some implementations, theadjustment may be based upon derived crop residue parameter values foundin a field map generated from the crop residue parameter values.

FIG. 4 is a flow diagram of an example method 200 for deriving a valuefor a crop residue parameter. Method 200 may be carried out byprocessing unit 152 following the analytical instructions 156 containedin medium 154. It should be appreciated that method 200 may likewise becarried out by analytical unit 26 or any of the analytical units orcontrollers described hereafter.

As indicated by block 204, processing unit 152, following analyticalinstructions 156, optically identifies individual pieces of cropresidue. For example, processing unit 162 may apply various opticalfilters to an image 55 or otherwise detect the edges of individualpieces of crop residue depicted in an image.

As indicated by block 208, processing unit 152, following analyticalinstructions 156, may measure the individual pieces using the detectededges of the individual pieces and the scale of the image beinganalyzed. The measurements of the individual pieces may be used togenerate a statistical average or other statistical value characterizingthe crop residue in the image 55. In some implementations, themeasurements may be compared to thresholds and the crop residue andimage may be categorized in terms of processing by harvester 22, interms of the type of crop residue or in terms of other predeterminedcategories.

FIG. 5 is a flow diagram of an example method 300 for deriving a valuefor a crop residue parameter. Method 300 may be carried out byprocessing unit 152 following the analytical instructions 156 containedin medium 154. It should be appreciated that method 200 may likewise becarried out by analytical unit 26 or any of the analytical units orcontrollers described hereafter.

Method 300 comprises a training and verification phase 302 and a usephase 304. In the training phase, a set of criteria is identified (oradjusted) for use in use phase 304. In the use phase 304, images of cropresidue captured by camera 24 (described above) are analyzed using thecriteria to derive a value for the particular image. The differentvalues for multiple images may be aggregated and used for adjusting orcontrolling a subsequent field operation.

As indicated by block 308, controller 150 receives first images of cropresidue (CR) that have been provided with ground truth category labelssuch as ground truthing mechanism labels or human based categorylabels.” “Ground truth” labels refer to labels assigned by directobservation or empirical evidence as opposed to being based uponinference. “Human based” means that the images have been assignedcategories or labels directly based upon visual inspection by humans.For example, persons may personally assign category labels to givenimages of crop residue. Ground truth labels may further include labelsthat have been derived from direct visual inspection. For example,reinforced learning algorithms and convolution neural nets may add totraining sets that provide ground truth values. As indicated by block312, the neural network forming control unit 50 may then opticallyanalyze the same images of crop residue and identify various categorycriteria for the different categories or labels based upon an opticalanalysis of the images and the ground truth category labels.

The training phase may also involve at least one verification andadjustment phase. As indicated by block 316, control unit 50 receives asecond set of images that also have been given ground truth categorylabels. Control unit 50 may then apply the identified category criteriato label the second images with analytical unit-based category labels.As indicated by block 320, the analytical unit-based category labels maybe compared against the human-based category labels to determine howclose the analytical unit-based category labels correspond to thehuman-based category labels. As indicated by block 324, based upon thiscomparison, controller 150 automatically adjusts the identified categorycriteria. This process outlined in block 308-324 may be iterativelyrepeated until the analytical unit-based category labels for a given setof images sufficiently match or correspond to the human-based categorylabels for the same set of images.

As indicated by block 328, following at least one training phase 302,controller receives an additional image of crop residue as captured bycamera 24 as the harvester is traversing a field during harvest. Asindicated by block 332, controller 150 may compare identifiedcharacteristics of the third image to the identified category criteriato assign a category to the crop residue of the third image. Theassigned category may be presented to an operator or may be used totrigger an adjustment to a subsequent field operation.

FIG. 6 is a schematic diagram of an example crop residue monitoringsystem 410. System 410 comprises combine harvester 422, cameras 424-1,424-2, 424-3, 424-4 and 424-5 (collectively referred to as cameras 424)and controller 450. Combine harvester 410 comprises a main frame 412having wheeled structure including front and rear ground engaging wheels414 and 415 supporting the main frame for forward movement over a fieldof crop to be harvested. The front wheels 414 are driven by anelectronically controlled hydrostatic transmission.

A vertically adjustable header or harvesting platform 416 is used forharvesting a crop and directing it to a feeder house 418. The feederhouse 418 is pivotally connected to the frame 412 and includes aconveyor for conveying the harvested crop to a beater 419. The beater419 directs the crop upwardly through an inlet transition section 422 toa rotary threshing assembly 421. In other implementations, otherorientations and types of cleaning structures and other types of headers416, such as transverse frame supporting individual row units, areutilized.

The rotary threshing assembly 421 threshes and separates the harvestedcrop material. Grain and crop residue, such as chaff, fall through aconcave 425 and separation grates 423 on the bottom of the assembly 421to a cleaning and separation system 426, and are cleaned by a chafferand/or sieve 428 and air fan or blower 429. The blower 429 blows thelighter crop residue above the sieve 228 rearwardly for discharge. Thegrain passes through openings, between louvers, provided by the sieve428. The clean grain is directed to elevator 433. Clean grain elevator433 conveys the grain to tank 442. The clean grain in the tank 442 canbe unloaded into a grain cart or truck by unloading auger. Tailings fallinto the return elevator or auger 431 and are conveyed to the rotor 437where they are threshed a second time.

Threshed and separated straw is discharged from the rotary threshingassembly 421 through an outlet 432 to a discharge beater 434. In oneimplementation, the discharge beater 434, in turn, propels the straw tothe rotary chopper 444 which chops the straw and other residue beforedirecting the straw and other residue to separator 446. In someimplementations where the straw is chopped by chopper 444, dischargebeater 434 may be omitted or other mechanism may be used to direct thestraw to rotary chopper 444. In yet other implementations, the dischargebeater 434 may direct the straw to a discharge outlet above spreader446, wherein the straw is not chopped prior to being discharged from therear of combine harvester 410 by spreader 446. The operation of thecombine is controlled from an operator's cab 435.

In the example illustrated, the rotary threshing assembly 421 comprisesa cylindrical rotor housing 436 and a rotor 437 located inside thehousing 436. The front part of the rotor and the rotor housing definethe infeed section 438. Downstream from the infeed section 438 are thecleaning section 439, the cleaning section 440 and the discharge section441. The rotor 437 in the infeed section 438 is provided with a conicalrotor drum having helical infeed elements for engaging harvested cropmaterial received from the beater 419 and inlet transition section 422.

In the cleaning section 439, the rotor 437 comprises a cylindrical rotordrum having a number of cleaning elements, sometimes called raspingbars, for cleaning the harvested crop material received from the infeedsection 438. Downstream from the cleaning section 439 is the cleaningsection 440 wherein the grain trapped in the threshed crop material isreleased and falls to the chaffer/sieve 428.

Cameras 424 comprise optical imaging devices that capture images of cropresidue (straw, chaff and other non-targeted portions of a crop plant orportions of harvested weeds) at various stages or times both prior toand following discharge of the crop residue from harvester 422. Camera424-1 captures images of crop residue moving between outlet 432 andchopper 444, upstream of spreader 446. In one implementation, camera424-1 is supported by frame 412 so as to be focused on a region withinthe harvester 422 between beater 434 and chopper 444.

Camera 424-2 is supported by frame 412 so as to be focused on interiorregions of harvester 422 so as to capture images of crop residue beingblown from chaffer/sieve 428 towards chopper 444 and toward spreader446.

Camera 424-3 is supported by frame 412 so as to focused on interiorregions of harvester 422 between chopper 444 and spreader 446. Camera424-3 captures images of crop residue after its been chopped by chopper444 and prior to being discharged and spread by spreader 446. FIG. 7 isan enlarged view illustrating one specific example for the positioningof camera 424-3. As shown by FIG. 7 , camera 424-3 may be supportedbetween chopper 444 and spreader 446 downstream a deflector 447.Deflector 447 comprises a ramp or other structure that directs the flowof crop residue over and above camera 424-3, reducing direct impactswith the camera and protecting camera 424-3 from the potentially cameradamaging flow of crop residue CR. FIG. 8 illustrates an alternativeimplementation which camera 424-3 is positioned below a transparentremovable and replaceable protective panel 448. Images from camera 424-3may indicate cracks or other damage to camera 424-3, providing noticefor replacing the panel 448. Panel 448 protects camera 424-3 from theflow of crop residue CR as it is being directed to spreader 446.

Camera 424-4 is mounted to frame 412 at a rear of harvester 422. Camera424-4 supported so as to be focused on the crop residue CR that is beendischarged onto the ground. In addition to providing an image depictingthe constitution of crop residue 42, camera 424-4 provides an image thatmay be used to determine the characteristics of the spread of cropresidue on the ground. In the example illustrated, crop residue 53 isspread by spreader 446 in a row tailing from harvester 422 as harvester422 traverses a field. As will be described hereafter, images producedby camera 424-4 may be used by controller 450 to identify the density ofdifferent widthwise portions of the row as well as to identify thedifferent constituents and different values for crop residue parametersfor each of multiple widthwise portions of the row, for examplewidthwise portions 453-1, 453-and 453-3.

Camera 424-5 is similar to camera 424-4 except that camera 424-5 is partof an airborne sensor 455. The airborne sensor 455 may be in the form ofa satellite, a drone, an airplane or other airborne vehicle or platform.Airborne sensor 455 may capture images of crop residue 53 after it hasbeen discharged or spread upon the ground trailing the path of harvester422 as a harvester 422 crosses the field.

Controller 450 may be in the form of controller 150 described above. Inone implementation, controller 450 is part of harvester 422. In yetanother implementation, controller 450 is a remote controller thatcommunicates in a wireless fashion to an onboard controller of harvester422 using a transceiver 451 (T) carried by harvester 422.

Controller 450 carries out both image analysis and control operations.Controller 450 receives signals from each of the cameras 424representing the captured images of the crop residue at the differentlocations. The analytical unit derives values for different crop residueparameters of the crop residue. In one implementation, controller 450may analyze the captured images pursuant to method 200 described above.In another implementation, controller 450 may analyze captured imagespursuant to method 300 described above.

Controller 450 further uses the derived values to present information toan operator regarding the crop residue. Controller 450 outputs controlsignals to a display 460 within cab 435 or at a remote operator controlstation. Controller 450 may present the derived statistical values forat least one parameter of the crop residue. For example, controller 450may present data regarding parameters such as crop residue moisture,average crop residue length, percentage of different crop residue typespresent in the crop residue. In some implementations, controller 450 maypresent the derived at each of the different locations or stages. Forexample, controller 450 may present on display 460 a first set of valuesfor different crop residue parameters derived from images captured bycamera 424-1, a second different set of values for the crop residueparameters derived from images captured by camera 424-2, a thirddifferent set of values for the crop residue parameters derived fromimages captured by camera 424-3, the fourth set of values for the cropresidue parameters derived from images captured by camera 424-4 and afifth different set of values for the crop residue parameters derivedfrom images captured by camera 424-5. The different values presented tothe operator may indicate the state of the crop residue at differentlocations as it passes through and his discharge from harvester 422.Such information may be utilized to evaluate the performance of variouscomponents of harvester 422.

In some implementations, the values for different parameters associatedwith the crop residue may be derived from an aggregation of valuesderived from images from multiple cameras 424. In other words, thevalues may be generated using the images from all of cameras 424 or morethan one camera 424. In such an implementation, controller 450 mayreceive input from an operator indicating which cameras 424 are toprovide the images that are used for deriving the crop residue parametervalues. In one implementation, controller 450 may further receive inputfrom an operator assigning a predefined weight to each camera, thedegree to which the values derived from each camera contribute to theoverall value for a particular crop residue parameter. For example, fora first parameter, the predefined weights assigned to the differentcameras may result in the individual values from camera 424-3 having alarger impact or effect on the aggregate value for the first parameteras compared to the individual values from a different camera, such ascamera 424-2.

As further shown by FIG. 6 , the different values for the differentparameters may be determined for individual widthwise portions of theoverall trailing row of crop residue discharged from harvester of 422.These different values may be presented on display 460. In the exampleillustrated, controller 450 outputs signals causing display 462 presenta graph having a first bar 461-1 displaying the derived values for acrop parameter for widthwise portion 453-1, a second bar 461-2displaying derived values for the crop residue parameter for widthwiseportion 453-2 and a third bar 461-3 displaying derived values for thecrop residue parameter for widthwise 453-3 of the discharged row of cropresidue. Such values may represent the density or mass for each of thedifferent widthwise portions as derived from images captured by camera424-4 and/or 424-5. Such values may also identify the moisture, degreeof chop or length of straw/residue for the different widthwise portions453. The different parameters represented by the example bar graph maybe reflected by an appropriate legend 462.

In addition to displaying or presenting the individual parameter valuesfor crop residue from each of the cameras and a category, score or othervalue derived from an aggregation of values from multiple cameras 424,controller 450 may compare such values against various thresholds totrigger the adjustment of the operational settings of harvester 422.Such adjustments may dynamically occur in real time as a harvester 422is crossing a field. In one implementation, based on a comparison of thevalue against various predetermined thresholds, controller 450 mayoutput control signals to an actuator 470 (such as a hydraulic orelectric motor) so as to adjust the speed of chopper 470 or the power ofchopper 470. Based upon such comparison, controller 450 may additionallyor alternatively output control signals to actuator 472 (such as ahydraulic cylinder or a solenoid) to adjust the position of the choppercounter knife 445 as indicated by arrow 473, wherein the positioningaffects the degree to which the residue is chopped by chopper 444. Basedupon such comparison, control unit 50 may additionally or alternativelyoutput control signals to actuator 474 (such as a hydraulic or electricmotor) to adjust the speed of spreader 446 or the positioning of itsvanes. Based upon such comparison, controller 450 may additionally oralternatively output control signals to actuator 476 adjusting theheader height, may output control signals to actuator 478 or actuator480 adjusting a threshing speed, separation speed, threshing clearanceor sieve louver positions. Based upon such comparison, controller 450may additionally or alternatively output control signals adjusting thespeed of harvester 422 crossing a field or the rate at which crops arefed through harvester 422 by the various augers, conveyors andcomponents of harvester 422.

As further shown by FIG. 6 , in some implementations, controller 450 mayutilize the derived values for the different crop residue parameters togenerate a crop residue field map 490 which may be stored for subsequentuse. The field map 490 may be utilized during subsequent harvestingoperations or for other field operations by agricultural machines orequipment other than harvester 422. For example, the field map 490 maybe utilized to adjust the operational settings of tillage equipment orapplicators that apply herbicide, insecticide or fertilizer. The fieldmap may be utilized to adjust the operational settings of a planter as aplanter is traversing a field.

Controller 450 may generate field map 490 based upon geo-referencingsignals that indicate the location of harvester 422 as it is traversinga field. In one implementation, controller 450 may receive signals froma global positioning satellite or system that indicates the particularlocation of harvester 422 as harvester 422 traverses the field. Thisgeo-referencing data may be linked to the associated values for thedifferent derived crop residue parameters. As shown by FIG. 6 , theresulting crop residue map 490 may represent a series of crop residuerows 492, each row 492 having particular geo-referenced locations andassociated with the particular crop residue parameter values derivedfrom images captured when harvester 422 was processing or dischargingcrop residue at the particular geo-referenced location.

As further shown by FIG. 6 , each geo-referenced row 492 and map 490 mayhave a widthwise resolution less than the width of the row 492. In theexample illustrated, each row 492 in map 490 may depict different valuesfor an individual crop residue parameter for different individualwidthwise regions or portions 453. Such values may change along thelength of each row 492 as a harvester 422 is crossing a field. In theexample illustrated, widthwise portion 453-1 is depicted in field map490 as having a first value or category 494-1 for a particularparameter, widthwise portion 453-2 is depicted in field map 490 ashaving a second different value 494-2 for the parameter and widthwiseportion 453-3 in field map 490 is depicted in field map 490 is having athird different value 494-3 for the particular crop residue parameter.Such values 494 change along the length of row 492. For example, thevalue for the particular parameter for region 453-1 changes from value494-1 to value 494-4 at geo-referenced location 495.

The different values for the crop residue parameter at the differentgeo-referenced locations may be utilized to adjust operationalsubsequent field operations. For example, based upon the data containedin field map 490, a tillage implement may operate at a first operationalsetting in a first geo-referenced location in the field may switch to asecond different operational setting for a second geo-referencedlocation the field based upon changes in the values for the crop residueparameter. A planter may plant seeds at a first depth at a firstgeo-referenced location in the field and at a second different depth ata second geo-referenced location in the field based upon differencesbetween the value of the crop residue parameter at the firstgeo-referenced location and the second geo-referenced location. Asprayer or other material applicator may apply herbicide, insecticideand/or fertilizer at a first rate at a first geo-referenced location ina field and a second different rate at a second geo-referenced locationthe field based upon differences between the value of the crop residueparameter at the first geo-referenced location and the secondgeo-referenced location. Different herbicides, insecticides and sensorfertilizers may be applied at the first geo-referenced location in thefield as compared to the second geo-referenced location in the fieldbased upon differences between the value of the crop residue parameterat the first geo-referenced location and the second geo-referencedlocation.

Although the present disclosure has been described with reference toexample implementations, workers skilled in the art will recognize thatchanges may be made in form and detail without departing from the spiritand scope of the claimed subject matter. For example, although differentexample implementations may have been described as including featuresproviding one or more benefits, it is contemplated that the describedfeatures may be interchanged with one another or alternatively becombined with one another in the described example implementations or inother alternative implementations. Because the technology of the presentdisclosure is relatively complex, not all changes in the technology areforeseeable. The present disclosure described with reference to theexample implementations and set forth in the following claims ismanifestly intended to be as broad as possible. For example, unlessspecifically otherwise noted, the claims reciting a single particularelement also encompass a plurality of such particular elements. Theterms “first”, “second”, “third” and so on in the claims merelydistinguish different elements and, unless otherwise stated, are not tobe specifically associated with a particular order or particularnumbering of elements in the disclosure.

What is claimed is:
 1. A crop residue monitoring system comprising: aharvester comprising a frame, a chopper and a spreader, the harvesterconfigured to separate a first portion of a crop plant from a secondportion thereof, wherein the chopper is configured to chop the firstportion of the crop plant into crop residue and direct a flow of thecrop residue toward the spreader; a camera coupled to the frame andlocated downstream of the chopper, the camera configured to capture animage of the flow of crop residue; and a structure located along theflow of crop residue, wherein the structure is configured to separatethe flow of crop residue from the camera.
 2. The system of claim 1wherein the camera is located downstream of the structure and betweenthe chopper and the spreader.
 3. The system of claim 1, wherein: theharvester defines an interior region between the chopper and thespreader; wherein the camera is configured to be focused on the interiorregion of the harvester.
 4. The system of claim 1, wherein the structurecomprises a deflector configured to deflect the flow of crop residueaway from the camera.
 5. The system of claim 4, wherein the deflectorcomprises a ramp.
 6. The system of claim 1, wherein the chopper definesa cavity configured to direct the flow of crop residue; wherein thestructure is located between the cavity and the camera.
 7. The system ofclaim 1, wherein the structure comprises a protective panel, the camerabeing adjacent to the protective panel such that the protective panel ispositioned between the camera and the flow of crop residue.
 8. Thesystem of claim 7, wherein the protective panel is removable orreplaceable.
 9. The system of claim 1, further comprising: an analyticalunit configured to derive a crop residue parameter of the crop residuebased upon an analysis of the image; and a controller configured toadjust a subsequent field operation based upon the value of the cropresidue parameter.
 10. The system of claim 9, wherein the analyticalunit derives the crop residue parameter by: optically identifyingindividual pieces of crop residue based upon the analysis of the image;and identifying a length of pieces of the crop residue, the crop residueparameter being based upon a count of a number of the pieces having eachof a plurality of lengths.
 11. The system of claim 10 wherein theanalytical unit comprises a neural network, wherein the neural networkderives category criteria for the crop residue parameter.
 12. The systemof claim 11 wherein the camera captures an additional image of the cropresidue and compares identified characteristics of the additional imageto the category criteria to trigger an adjustment to the subsequentfield operation.
 13. A method for harvesting a crop plant comprising:separating a first portion of the crop plant from a second portionthereof; forming crop residue from the first portion of the crop plant;directing a flow of the crop residue away from the chopper toward aspreader; protecting the camera from the flow of crop residue via astructure located between the chopper and the spreader; imaging the flowof crop residue with a camera, wherein the camera captures an image ofthe flow of crop residue; analyzing the captured image to derive a cropresidue parameter of the crop residue; and adjusting a harvestingoperation of the harvester based on the derived crop residue parameter.14. The method of claim 13, further comprising supporting the camera onthe harvester between the chopper and the spreader.
 15. The method ofclaim 14, further comprising focusing the camera on an interior regionof the harvester located between the chopper and the spreader.
 16. Themethod of claim 13, wherein the structure comprises a deflector andwherein protecting the camera from the flow of crop residue via astructure located between the chopper and the spreader comprisesdirecting the flow of crop residue away from the camera with thedeflector.
 17. The method of claim 13, wherein the structure comprises aramp and wherein protecting the camera from the flow of crop residue viaa structure located between the chopper and the spreader comprisesdirecting the flow of crop residue away from the camera with the ramp.18. The method of claim 13, wherein the structure is a protective paneland wherein protecting the camera from the flow of crop residue via astructure located between the chopper and the spreader comprisesseparating the flow of crop residue from the camera with the protectivepanel.
 19. The method of claim 18, wherein the protective panelcomprises a transparent protective panel.
 20. The method of claim 13,adjusting a harvesting operation of the harvester based on the derivedcrop residue parameter comprises one of adjusting a speed of the chopperor adjusting a position of a chopper counter knife.